&lt;b&gt;GENES - a software package for analysis in experimental statistics and quantitative genetics&lt;/b&gt; - doi: 10.4025/actasciagron.v35i3.21251

Cruz, Cosme Damião

doi:10.4025/actasciagron.v35i3.21251

Cited by 1,585 publications

(1,494 citation statements)

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“…Regression models were chosen based on the significance of the model and coefficients, using Student's t-test (p≤0.05); also considering the coefficient of determination (R²). Data analysis was performed using the statistical software "GENES" (Cruz, 2013).…”

Section: Resultsmentioning

confidence: 99%

Aluminum stress in Crambe abyssinica Hochst

Colodetti

Rodrigues

Martins

et al. 2015

Idesia

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Crambe is a sensitive specie to exchangeable aluminum, it require a well-fertilized and corrected soil. The objective of this study was to understand the impact of aluminum presence, in different concentrations, in the substrate on the germination and development of crambe. The experiment was carried out as a randomized complete block design with a 5x2 factorial arrangement in four replicates. The five concentrations of Al 3+ were 0, 15, 40, 80 and 120 mg dm -3 Al 3+ and two temperatures (20 and 30 °C), with four replications. The relative growth rate, plant height, leaf number, total leaf area, specific leaf area, dry matter in each plant compartment (root, stem and leaf), leaf area ratio, stem mass ratio and leaf mass ratio were evaluate. Germination was favored by 20 ºC. The limitation on plant growth was greater as the concentration of aluminum increased, presenting losses in growth, as well of production of dry matter and leaf development, also causing changes in the patterns of biomass allocation between the plant compartments.Keywords: crambe, toxicity, germination, growth. RESUMEN Crambe es una especie sensible al aluminio intercambiable que requiere suelos bien fertilizados y corregidos. El objetivo de este trabajo fue evaluar distintas concentraciones de aluminio en la germinación y desarrollo de crambe. El experimento para germinación se realizó con un diseño de bloques completos al azar con arreglo factorial de 5x2, con cuatro repeticiones. Las cinco concentraciones de

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Section: Resultsmentioning

confidence: 99%

Aluminum stress in Crambe abyssinica Hochst

Colodetti

Rodrigues

Martins

et al. 2015

Idesia

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“…The method of Mojema using k = 1.25 (Cruz et al, 2013) indicated a cut at 80.37% of the genetic dissimilarity defining four groups. The first group gathers the cultivars with the initials B3; other group gathers the genotypes with the initials CS and UFV except UFVS2012; DM339 and MSOY6101 form another group, and the remaining group includes BARC-8 and BR8014887 which have high protein contents.…”

Section: Discussionmentioning

confidence: 99%

“…The combined analysis of variance was performed using the software Genes (Cruz, 2013) and the statistical model proposed in Equation 1.…”

Section: Methodsmentioning

confidence: 99%

“…The genetic distance (Bonato, Calvo, Arias, Toledo & Geraldi, 2006) estimates obtained by the complement of the weighted similarity index from the 39 microsatellite markers were also compared to the estimates obtained by the same index from the microsatellites of linkage group I, linkage group most related to the protein content according to the literature (Grant et al, 2010). All mentioned analyzes were performed with the sotware GENES ® (Cruz, 2013), to identify significant difference among treatments and statistical significance for all comparisons was made at p<0.05. Tukey's multiple range test was used to compare the mean values of treatments.…”

Section: Equationmentioning

confidence: 99%

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et al. 2017

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Pre-mejoramiento vegetal para el volumen incrementado de proteína en soya Glycine max (L. ) AbstractThe aim of this research were to determine protein content and genetic divergence of soybean genotypes in QTL regions of the trait grain protein content for plant breeding purposes. Twenty-nine soybean genotypes were grown in the field in four environments (Viçosa-MG Dec/2009, Visconde do Rio Branco-MG Feb/2010, São Gotardo-MG Feb/2010, and São Gotardo-MG Oct/2011) using the randomized block design with three replicates. The grain protein content was quantified by the infrared spectrometry method. The genetic divergence was estimated by the analysis of 39 microsatellite markers from QTL regions for the soybean grain protein content. The pairs of genotypes with greater genetic distances and protein contents were as follows: BARC-8/CS3032PTA276-3-4 (D=0.71) (45.18%/44.31%); BARC-8/CS3032PTA276-1-2 (D=0.71) (45.18%/43.75%); BARC-8/CS3032PTA190-5-1 (D=0.71) (45.18%/43.63%); B3PTA382-2-10/CS3032PTA276-3-4 (D=0.62) (43.80%/44.31%); CS3032PTA276-1-2/ B3PTA382-2-10 (D=0.62) (43.75%/43.80%); B3PTA382-2-10/CS3032PTA190-5-1 (D=0.62) (43.80%/43.63%); B3PTA216-1-9/CS3032PTA276-3-4 (D=0.61) (43.48%/44.31%); and B3PTA216-1-9/CS3032PTA276-1-2 (D=0.61) (43.48%/43.75%), respectively. Other promising combinations for the improvement of protein content were as follows: BR8014887/CS3032PTA190-5-1 (D=0.57) (44.71%/43.63%); BARC-8/CS3032PTA182 (D=0.78) (45.18%/41.84%); BR8014887/CS3032PTA182 (D=0.65) (44.71%/41.84%); BR8014887/PI417360 (D=0.76) (44.71%/41.01%), respectively; and PI417360/B3PTA216-1-9 (D=0.80) (41.01%/43.48%). These pairs of genotypes when crossed should produce populations with higher means and genetic variances and greater gains with selection.

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“…In agricultural research, in general, and in the genetic breeding area, in particular, many products have been generated within the scope of this motivation, both to implement techniques related to statistical methods and simulation, and to particularize or specialize these and other techniques (RESENDE, 2007;CRUZ, 2013;FERREIRA, 2013). From these initiatives and the aggregation of advanced computational techniques, the area of bioinformatics has emerged mainly related to the area of molecular biology, and more particularly, to applications in genomic selection and genome-wide selection (LEGARRA et al, 2009;GARRICK;SAATCHI, 2011).…”

Section: Introductionmentioning

confidence: 99%

Guaiaca – a software tool for supporting the use of scientific applications designed for data analysis – part I: execution assistant

Medeiros

Barros

Dionello

2016

SCA

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The aim of this work is to develop a software tool that provides a user-friendly graphical interface of generic and configurable design in order to ease the researcher's tasks in data manipulation and analysis. Two primary targets have influenced the design: data preparation for analysis in animal breeding programs and usability increase for those applications that perform important analysis methods, but interact with users only through text files and command lines. The Guaiaca tool was designed as a "utility belt" in the form of two integrated assistants, and it can be combined with multiple analysis applications. This tool offers facilities to: (a) collect, manipulate, and reorganize data; (b) organize, register, and retrieve analyses through descriptors; and (c) prepare and activate analysis processes. Guaiaca's Execution Assistant module is described in this paper, where is also emphasized the parameters to configure, the main data structures to maintain, and the form of the relationship between its generic interface and combined analysis applications. The generic interface has been customized and validated for the peculiarities of two applications, WOMBAT (mixed models) and INTERGEN (Bayesian models). Several data analyses were performed with the interface support to prove its generality and ease of installation, configuration and operation. Data sets from 5,726 quails in a breeding program were used with these applications. Use of the integrated Guaiaca-WOMBAT application is illustrated with an analysis example, prepared and visualized on the Guaiaca tool and executed by WOMBAT. The Beta version of the Guaiaca tool for Windows is available free of charge to the scientific community and can be obtained at http://wp.ufpel.edu.br/gilmedeiros/guaiaca. Key words: Animal breeding. Data analysis. History of analysis. Mixed models. Scientific software. Usability. ResumoO objetivo deste trabalho foi desenvolver uma ferramenta de software com interface gráfica amigável, genérica e configurável, para facilitar pesquisadores na organização e gerenciamento das atividades de manipulação e análises de dados. A concepção foi baseada nas características de dois focos principais: a preparação de dados para análises em pesquisas de melhoramento genético de animais e o incremento da usabilidade para aplicativos que implementam importantes métodos de análises, mas interagem com o usuário via arquivos de texto e linha de comando. A ferramenta Guaiaca foi modelada como um "cinto de utilidades" e desenvolvida na forma de dois assistentes integrados. Pode ser combinada

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<b>GENES - a software package for analysis in experimental statistics and quantitative genetics</b> - doi: 10.4025/actasciagron.v35i3.21251

Cited by 1,585 publications

References 28 publications

Aluminum stress in Crambe abyssinica Hochst

Aluminum stress in Crambe abyssinica Hochst

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Guaiaca – a software tool for supporting the use of scientific applications designed for data analysis – part I: execution assistant

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